The effect of job satisfaction and moonlighting intentions with mediating and moderating effects of commitment and HR practices an empirical study

The study investigates why and how employees in IT-enabled industries form intentions to moonlight (hold a second job), a trend amplified by remote work during COVID-19. Prior work highlights financial needs, career development, flexibility, and personal fulfillment as drivers, alongside potential conflicts of interest and work–life balance issues. The research aims to clarify inconsistent findings and examine underexplored mechanisms—specifically economic intentions and HR practices—linking job satisfaction to moonlighting intentions. The authors test whether job satisfaction influences organizational commitment and moonlighting intentions, whether organizational commitment and economic intentions mediate these relationships, and whether HR practices moderate the job satisfaction–moonlighting intentions link in the Hyderabad IT-enabled sector.

The review synthesizes evidence that organizational commitment generally reduces moonlighting intentions (e.g., studies among teachers and higher education faculty), while job satisfaction correlates with commitment and may relate to moonlighting intentions with mixed directions across contexts. Research emphasizes financial/economic strain, entrepreneurial motivation, autonomy, and skill diversification as key motives for multiple jobholding. Systematic reviews suggest varied motives including financial, career development, psychological fulfillment, and flexibility. Studies in education and IT contexts report that higher job satisfaction tends to reduce withdrawal cognitions but may coexist with moonlighting under certain conditions. The literature also addresses managerial and policy challenges of moonlighting, highlighting the need for clear HR policies. Identified gaps include limited examination of economic intentions as a mediator and the moderating role of HR practices in the job satisfaction–moonlighting link, particularly within IT-enabled settings.

Design: Cross-sectional survey with structural equation modeling (SEM). Setting and sample: IT-enabled industry professionals in and around Hyderabad, India. An online questionnaire link was shared with 800 employees; 350 responses were received; 311 valid responses were retained (39 discarded for response quality/incompleteness). Sampling size rationale used Cochran (1977) and a measurement-items heuristic (50 + 5x; x=21), with 311 exceeding minimum requirements for SEM. Demographics included balanced gender (49.5% male, 50.5% female), varied ages, education levels, and work experience. Measures: Five reflective latent constructs measured on 5-point Likert scales (1=strongly disagree to 5=strongly agree). Job satisfaction adapted from Huddleston and Good (1999). Organizational commitment adapted from Mowday et al. (1979). Economic intentions items developed by modifying Jehan et al. (2021) moonlighting scale. HR practices items adapted from Khatri and Khushboo (2014) and Demo et al. (2012). Moonlighting intentions adapted and modified from Seema and Sachdeva (2020). Reliability and validity: Pilot testing assessed interrater reliability, test–retest, and internal consistency (Cronbach’s alpha). EFA conducted; items with loadings <0.6 were removed; ECON4 was dropped for wording issues. Final model included 5 constructs and 21 indicators. KMO=0.796; Bartlett’s test p<0.001; five components explained 71.99% variance. Normality assessed via Shapiro–Wilk, skewness (−2 to +2) and kurtosis (−7 to +7) within recommended ranges. CFA/measurement model: Good fit (Table-reported indices): CMIN/DF=2.268; CFI=0.941; IFI≈0.939; TLI≈0.935; NFI=0.921; RMSEA=0.048; SRMR=0.049. Factor loadings mostly >0.7 (one retained at 0.66 given construct AVE>0.5). Reliability: Cronbach’s alpha >0.70 for all constructs; composite reliability 0.811–0.901. Convergent validity: AVE≥0.589 (threshold 0.50). Discriminant validity: Fornell–Larcker satisfied; HTMT values <0.85. Common method bias: Harman’s single-factor test and latent method factor comparison indicated minimal CMB (Δχ2≈4.5 not substantively concerning). Structural model: SEM in AMOS tested hypothesized paths, multiple mediation (Preacher and Hayes, 2008 approach via AMOS estimands) with organizational commitment and economic intentions as mediators, and moderation by HR practices following Hair et al. (2021), including interaction and direct effects. Model fit for structural model matched measurement fit thresholds. R-squared: Moonlighting intentions R2=0.50; Organizational commitment R2≈0.73.

- Model fit: CMIN/DF=2.268; CFI=0.941; IFI≈0.939; TLI≈0.935; NFI=0.921; RMSEA=0.048; SRMR=0.049, indicating excellent fit. - Explained variance: Moonlighting intentions R2=0.50; Organizational commitment R2≈0.73. - Direct effects (SEM): • Job satisfaction → Organizational commitment: β=0.346, t=4.180, p<0.001 (positive, significant). • Organizational commitment → Moonlighting intentions: β=−0.117, t=−2.673, p<0.05 (negative, significant). • Job satisfaction → Moonlighting intentions: β=0.741, t=9.713, p<0.001 (positive, significant). • Job satisfaction → Economic intentions: β=0.090, t=1.742, p>0.05 (not significant). • Economic intentions → Moonlighting intentions: β=0.058, t=0.876, p>0.05 (not significant). - Mediation: • Organizational commitment partially mediates the job satisfaction → moonlighting intentions relationship: indirect effect β=−0.039, t=−1.982, p<0.05; partial mediation confirmed. • Economic intentions do not mediate the job satisfaction → moonlighting intentions link: indirect effect β=0.038, p=0.511 (ns). - Moderation (HR practices): • HR practices → Moonlighting intentions (direct): β=0.306, CR=7.128, p<0.01 (positive, significant). • Interaction (Job satisfaction × HR practices) → Moonlighting intentions: β=0.052, CR=3.178, p<0.05 (significant). Simple slope shows stronger positive JS–moonlighting link at higher, employee-friendly HR practices. - Measurement quality: • Composite reliability: 0.811–0.901; AVE: 0.589–0.675; HTMT<0.85; factor loadings mostly >0.7; KMO=0.796; Bartlett p<0.001.

The findings support the hypothesized mechanism whereby higher job satisfaction increases organizational commitment, and greater commitment in turn reduces moonlighting intentions. Notably, job satisfaction also directly and positively predicts moonlighting intentions, suggesting that in IT-enabled contexts with flexible arrangements, satisfied employees may still pursue second jobs for reasons beyond dissatisfaction, such as skill development or opportunity seeking. The negative path from organizational commitment to moonlighting intentions indicates that strengthening commitment can mitigate this tendency. Economic intentions did not significantly explain moonlighting in this sample, implying that financial motives were less salient than attitudinal and organizational-context factors. HR practices significantly strengthened the positive relationship between job satisfaction and moonlighting intentions, indicating that employee-friendly, flexible HR policies can enable or legitimize side work, amplifying intentions among satisfied employees. These results clarify mixed prior findings by highlighting the dual role of job satisfaction (enhancing commitment yet also directly encouraging moonlighting) and by identifying HR practices as a key contextual moderator. The study has practical relevance for HR policy: organizations can reduce undesirable moonlighting by bolstering affective/normative commitment and offering internal opportunities, while carefully designing policies that balance flexibility with performance, confidentiality, and conflict-of-interest safeguards.

This study contributes by modeling and empirically validating a framework linking job satisfaction, organizational commitment, HR practices, and economic intentions to moonlighting intentions among IT-enabled employees. It shows that organizational commitment partially mediates, and HR practices positively moderate, the relationship between job satisfaction and moonlighting intentions, while economic intentions do not significantly mediate. The work underscores the importance of HR policy design and commitment-building to manage moonlighting. Practical recommendations include offering career advancement opportunities and fair compensation to reduce the need for external side work; permitting moonlighting under transparent policies that prevent conflicts of interest and protect performance and IP; and leveraging moonlighting to identify multitasking capabilities where appropriate. Future research should use larger and more diverse samples, extend to other industries, test serial/complex mediations and additional moderators, and examine post-pandemic dynamics and policy impacts across legal contexts.

- Context limited to IT-enabled companies in India; generalizability to other industries and countries is constrained. - Cross-sectional survey with self-reported measures may involve common method bias and personal/researcher bias despite mitigation steps. - Sample size of 311, though sufficient for SEM, limits broader generalization; convenience/online sampling may introduce response biases. - Focus on five constructs; other relevant variables (e.g., personality, job demands/resources, compensation structures) were not included. - Measurement relied on adapted scales; one economic intentions item was dropped; potential construct undercoverage. - Results reflect the pandemic and remote-work period; temporal changes were not captured.